Tracking and Preventing Diseases with Artificial Intelligence

This book presents an overview of how machine learning and data mining techniques areused for tracking and preventing diseases. It covers several aspects such asstress level identification of a person from his/her speech,automatic diagnosis of disease from X-ray images,intelligent diagnosis of Glaucoma from clinical eye examination data, prediction of protein-coding genes from big genome data, disease detection through microscopic analysis of blood cells,information retrieval from electronic medical record using named entity recognition approaches, and prediction ofdrug-targetinteractions. The book is suitable forcomputer scientists having a bachelor degree in computer science. The bookis an ideal resource as a reference book for teaching a graduate course on AI for Medicine or AI for Health care.Researchers working in the multidisciplinary areasuse this book to discover the current developments. Besides itsuse in academia, this book provides enough details about the state-of-the-art algorithms addressing various biomedical domains, so that it could be used by industry practitioners who want to implement AI techniques to analyze the diseases.Medical institutions usethis book as reference material andgive tutorials to medical experts on how the advanced AI and ML techniquescontribute to the diagnosis and prediction of the diseases.